
import matplotlib.pyplot as plt

plt.figure(figsize=(10, 5))

plt.plot([0, 1, 2, 3, 4], [0,1.2, 2, 5, 4], 'g-', label='Rat Weight')

plt.title('Average Rat Weight/Age')
plt.xlabel('Rat Age')
plt.ylabel('Rat Weight')
plt.xlim(0, 5)
plt.ylim(0, 20)
plt.grid(True)
plt.legend()

plt.show()


import numpy as np

plt.style.use('_mpl-gallery')

x = 0.5 + np.arange(8)
y = [4.8, 5.5, 3.5, 4.6, 6.5, 6.6, 2.6, 3.0]

fig, ax = plt.subplots()

ax.stem(x, y)

ax.set(xlim=(0, 8), xticks=np.arange(1, 8),
       ylim=(0, 8), yticks=np.arange(1, 8))

plt.show()


import plotly
import plotly.express as px

plotly.offline.init_notebook_mode()
df = px.data.tips()
fig = px.pie(df, values='tip', names='day')
fig.show()


import plotly.graph_objects as go
np.random.seed(1)

N = 70

fig = go.Figure(data=[go.Mesh3d(x=(70*np.random.randn(N)),
                   y=(55*np.random.randn(N)),
                   z=(40*np.random.randn(N)),
                   opacity=0.5,
                   color='green'
                  )])

fig.update_layout(
    scene = dict(
        xaxis = dict(nticks=4, range=[-100,100],),
                     yaxis = dict(nticks=4, range=[-50,100],),
                     zaxis = dict(nticks=4, range=[-100,100],),),
    width=700,
    margin=dict(r=20, l=10, b=10, t=10))

fig.show()


from PIL import Image

img = Image.open('ideogram.jpeg')
fig = plt.imshow(img)
plt.axis('off')

(-0.5, 1023.5, 1023.5, -0.5)

Average Rat Weight Per Age Table¶

A stem plot draws lines perpendicular to a baseline at each location locs from the baseline to heads, and places a marker there.¶

Plotly.Express is the easy-to-use, high-level interface to Plotly, which operates on a variety of types of data and produces easy-to-style figures.¶

3D Axes in python have an attribute in layout called scene, which contains attributes such as xaxis, yaxis and zaxis parameters, in order to set the range, title, ticks, color etc. of the axes.¶

An Image of a Cute snoop dog as a puppy¶